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Ways to successfully integrate AI
Companies face the challenge of identifying and building AI competencies in order to successfully integrate this future-oriented technology. The effective use of AI in companies is directly related to the existing skills in the team. The slow adoption of AI technologies can be largely attributed to a lack of specific skills. The KARL competence center creates transparency and skills development here. In a current project, practical materials are being developed for the independent identification of possible competence deficits.
Ariane Lindemann in conversation with Marco Baumgartner from Karlsruhe University of Applied Sciences, who runs the KARL research field together with the Fraunhofer Institute for Systems and Innovation Research (ISI). “Competencies for and through AI” directs.
What skills do companies and their employees need to successfully introduce AI technologies and use them effectively in the work environment?
The requirements are diverse: On the one hand, decision-making skills are required to evaluate an AI solution from different perspectives and decide accordingly on its introduction. This is followed by the implementation phase, which requires both technical skills to develop the technology and soft skills to coordinate and communicate. In the subsequent usage phase, specific skills are necessary for the users. The entire process requires sound project management with specific technical and non-technical skills to ensure the successful introduction and use of AI.
How can companies achieve this?
Step 1 would be to determine the competency needs of the workforce in dealing with AI technologies. The need varies depending on the use case of the AI and the general conditions of the company. First of all, it is important to be aware of which skills are relevant. The internal and externally available competencies are then analyzed, for example through workshops and service providers.
What does the KARL Competence Center offer?
KARL offers its own workshops in which companies can identify specific skills for their use case. An additional tool is KARL’s AI benchmark, which analyzes relevant competencies in the AI context in terms of importance and availability based on the ratings of 215 company representatives. This allows companies to specifically rely on similar framework conditions from other companies and determine the needs for their application. Based on these insights, they can then target training or hire staff to meet the greatest needs.
What is the current staffing level of companies with regard to the skills to implement and use AI technologies?
There are some challenges here. While specific, technical AI knowledge is rarely available internally, it can be purchased externally, particularly in the area of development skills. What makes it more difficult, however, is the lack of basic AI knowledge in companies. This deficit requires internal expertise to guide external partners and develop realistic expectations for the overall project. In addition, there is often a lack of “soft” skills to involve people who understand the process and have the necessary process knowledge. This is crucial to enable active participation in decisions and interdisciplinary collaboration. In AI projects in which technicians with specific technical jargon and users without previous AI experience come together, mediation between these groups is experienced as non-trivial.
It is not uncommon to encounter fears among employees here…
In fact, there are many fears here, for example about job loss, data protection concerns, or the black box character that artificial intelligence brings with it, which has something mystified for many that can cause fears. Companies must also be able to address these fears and have an appropriate set of soft skills.
How could the general understanding of AI in companies be improved, from management to employees, especially given the wide range of AI applications that go beyond chatbots?
It is important to create broader awareness of artificial intelligence by showing not only managers but also employees that AI is more than just chatbots. “While the term AI in the past primarily evoked associations with humanoid robots, today many people immediately think of ChatGPT when they hear AI. Companies should therefore strive to promote a broader understanding of AI among their employees in order to better communicate the variety of possible applications.
What contribution does the research field “Competencies for and through AI” make to this?
The project makes a significant contribution to determining the skills needs of companies and identifying skills gaps with the help of a developed analysis grid. On this basis, targeted further training offers can be developed. The training offering includes modules to teach AI basics and skills, highlighting technical, organizational and human-centered perspectives. Companies can book these training courses on a modular basis in order to impart targeted basic knowledge. In addition to training, KARL also offers workshops on implementation strategies, transparency, explainability, data protection as well as ethical, legal and social aspects. In addition, the project provides tools and assistance for companies on its homepage.
What happens after the project ends?
The project is planned until at least 2025 and will then be continued as an independent business model. The services offered are currently free as they are being tested as part of the research project. However, it is planned for the future that the competency model will be self-sustaining – both through services and through various other offers and assistance.
What are the project findings intended for?
We use the knowledge gained as a basis to promote understanding of AI in companies and universities by developing, testing and evaluating practice-oriented teaching and learning methods. KARL sees the application of intelligent knowledge-based systems as a significant opportunity for innovation in the education sector. In particular, the possibility of offering AI-supported individualized content is seen as a potential for the development of skills through AI.
The knowledge gained should be disseminated in practice through lectures, conferences and workshops in order to inform and raise awareness. At the same time, they should contribute to broadly promoting understanding of AI through scientific publications. In addition, the findings are used in teaching to provide students with relevant information and a corresponding mindset who could later take on responsibility in similar projects.
About KARL
KARL’s goal is to design AI-supported work and learning systems in a human-centered, transparent and learning-conducive manner and to make them demonstrable in concrete practical applications. The project is aimed at companies, employees and interested parties in the Karlsruhe region who use AI-supported work and learning systems, deal with them or want to understand them better. KARL is one of currently eight regional competence centers that deal with the effects of artificial intelligence (AI) on the world of learning and work.
The CyberForum is part of the project consortium and is primarily responsible for public relations, community management and the sustainability concept. The consortium leader is Karlsruhe University of Applied Sciences. In addition to nine research and transfer partners, the project partners also include eleven regional companies.
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Marco Baumgartner
is a research associate at the Institute for Learning and Innovation in Networks (ILIN) at Karlsruhe University of Applied Sciences. He is a member of the research project KARL (Artificial Intelligence for Work and Learning in the Karlsruhe Region) and head of the KARL design field “Competencies for and through AI”. In addition, as part of his doctorate, he is working on socio-technical issues in the areas of human-technology trust, sustainability in technology introductions in companies and technology-supported knowledge management.